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Knowing the genes involved in quantitative traits provides an entry point to understanding the biological bases of behavior, but there are very few examples where the pathway from genetic locus to behavioral change is known. To explore the role of specific genes in fear behavior, we mapped three fear-related traits, tested fourteen genes at six quantitative trait loci (QTLs) by quantitative complementation, and identified six genes. Four genes, Lamp, Ptprd, Nptx2, and Sh3gl, have known roles in synapse function; the fifth, Psip1, was not previously implicated in behavior; and the sixth is a long non-coding RNA, 4933413L06Rik, of unknown function. Variation in transcriptome and epigenetic modalities occurred preferentially in excitatory neurons, suggesting that genetic variation is more permissible in excitatory than inhibitory neuronal circuits. Our results relieve a bottleneck in using genetic mapping of QTLs to uncover biology underlying behavior and prompt a reconsideration of expected relationships between genetic and functional variation.

Sheath blight, caused by Rhizoctonia solani, severely affects rice, causing 20–69% yield losses in tropical and temperate regions. Key challenges include the pathogen's broad host range, persistent sclerotia, climate change, and the reliance on semi-dwarf varieties. The disease's complex inheritance and lack of highly resistant cultivars hinder management, making resistant variety breeding a sustainable solution. This study mapped sheath blight resistance Quantitative trait locus (QTLs) from PAU-shb8, a moderately resistant rice line. This line exhibited moderate resistance with a disease score of 3 (RLH < 20%), whereas susceptible rice cultivar PR121 scored 9 (RLH > 60%). Screening of 1160 plants from BC1F5 and BC1F6 populations revealed 50.34% as moderately resistant, 37.76% moderately susceptible, and 11.88% susceptible. (QTL) mapping using 4622 SNP markers identified 20 QTLs across eight traits, with significant loci on chromosomes 2, 4, 6, 8, 9, 10, 11, and 12. Chromosome 12 harbored a cluster of QTLs associated with multiple traits, including RLH, lesion height, and disease score, while chromosome 8 exhibited a major QTL for RLH with a LOD score of 9.8 and 9.2% phenotypic variance. Genomic analysis pinpointed candidate genes related to resistance, such as leucine-rich repeat proteins and calcium/calmodulin-dependent protein kinases. Promising genotypes 7168, 7183, and 7152 demonstrated moderate resistance, combining key QTLs for RLH, disease severity, and lesion height with favorable agronomic traits. These backcross inbred lines are pivotal for breeding sheath blight-resistant rice varieties and for the expansion of resistance gene pool of sheath blight. [ABSTRACT FROM AUTHOR]

Foxtail millet (Setaria italica) is one of the most ancient cultivated cereal crops and is ideal for the functional genomics of the Panicoideae crops. In the present study, we generated an F2 population consisting of 300 individuals by crossing an elite foxtail millet variety Jingu28 with a backbone line Ai88, and constructed a genetic linkage map with 213 published SSR markers and two InDel markers. Quantitative trait locus (QTL) mapping identified 46 QTL for 12 agronomic traits, including 13 major effect QTL. Meanwhile, 40 QTL controlling different traits formed 13 co-located QTL clusters. Moreover, one putative candidate gene Seita.9G020100 for qHD9-1 with conserved CCT motif and a gibberellin biosynthesis related GA20 oxidase gene Seita.5G404900 for qPH5-1 were identified based on homologous gene comparison. The 277 bp insertion/deletion on the promoter of Seita.9G020100 and the one-base (G) insertion/deletion in the third exon of Seita.5G404900 might be candidate functional sites. Furthermore, two markers (Ghd7InDel and GA20oxSTARP-1) were developed based on these two variation sites, respectively. These results will help to elucidate the genetic basis of important agronomic traits in foxtail millet and be useful for marker-assisted selection of varieties with ideal plant architecture and high yield potential. [ABSTRACT FROM AUTHOR]

Ovule number per ovary (ONPO) determines the maximum potential of seed number per fruit that is a direct component of seed yield in crops. This study aimed to dissect the genetic basis and molecular mechanism of ONPO using a newly developed doubled haploid (DH) population in oilseed rape. In all the four investigated environments, the ONPO of 201 DH lines exhibited normal distribution with a wide variation from 22.6 to 41.8, suggesting quantitative inheritance appropriate for mapping QTL. A skeleton genetic map of 2111 markers within 19 linkage groups was developed, with a total of 1715.71 cM in length and an average of 0.82 cM between markers. Linkage mapping identified ten QTLs that were distributed on eight chromosomes and explained 7.0-15.9% of the phenotypic variance. Among these, four were identical to the reported and two were repeatedly detected with relatively large effects, highlighting their potential for marker-assisted selection. Phytohormone quantification of ovaries (at the ovule initiation stage) from two pools of high and low ONPO lines showed significant differences in the levels of nine sub-types of phytohormones, suggesting their important roles in regulating ovule number. Transcriptomic analysis identified 7689 differentially expressed genes (DEGs) between the two pools, of which nearly half were enriched into functional categories of reported genes regulating ONPO, including protein, RNA, signalling, miscellaneous, development, hormone metabolism, and tetrapyrrole synthesis. Integration of linkage QTL mapping, transcriptome sequencing and BLAST analysis identified 15 homologues of reported ovule number genes and 327 DEGs in the QTL regions, which were considered as direct and potential candidate genes. These findings propose further insights into the genetic basis and molecular mechanisms of ONPO, which will facilitate future gene cloning and genetic improvement for enhancing seed yield in oilseed rape. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shenyang Agricultural University is the property of Journal of Shenyang Agricultural University Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Starch is the most abundant carbohydrate in maize grains, serving as a primary energy source for both humans and animals, and playing a crucial role in various industrial applications. Increasing the starch content of maize grains is beneficial for improving the grain yield and quality. To gain insight into the genetic basis of starch content in maize kernels, a multiparent population (MPP) was constructed and evaluated for starch content in three different environments. Results: The integration of QTL mapping and genome-wide association analysis (GWAS) identified two SNPs, 8_166371888 and 8_178656036, which overlapped the QTL interval of qSC8-1, identified in the tropical maize line YML46. The phenotypic variance explained (PVE) by the QTL qSC8-1 was12.17%, while the SNPs 8_166371888 and 8_178656036 explained 10.19% and 5.72% of the phenotypic variance. Combined GWAS and QTL analyses led to the identification of two candidate genes, Zm00001d012005 and Zm00001d012687 located on chromosome 8. Conclusions: The candidate gene Zm00001d012005 encodes histidine kinase, which is known to play a role in starch accumulation in rice spikes. Related histidine kinases, such as AHK1, are involved in endosperm transfer cell development in barley, which affects grain quality. Zm00001d012687 encodes triacylglycerol lipase, which reduces seed oil content. Since oil content in cereal kernels is negatively correlated with starch content, this gene is likely involved in regulating the starch content in maize kernels. These findings provide insights into the genetic mechanisms underlying kernel starch content and establish a theoretical basis for breeding maize varieties with high starch content. [ABSTRACT FROM AUTHOR]

In the rapid climate change scenario and subsequent rainfall patterns, drought has emerged as a bottleneck for crop production across crops, especially in rainfed rice. Drought significantly affects the development and production of most modern rice cultivars. Thus, recent breeding efforts have aimed to integrate drought tolerance traits in existing rice varieties through conventional and molecular approaches. The identification of grain yields quantitative trait loci (QTLs) under drought conditions, an important trait with high selection efficiency, may lead to the development of drought-tolerant rice varieties. The study reported the grain yield QTLs identified under the reproductive stage of drought stress in the F2-derived mapping population from Kasturi (drought-sensitive) × Chao Khaw (drought-tolerant). Thirteen QTLs (qDTYs) were identified based on two years of field data. Comparative analysis revealed two robust and consistent DTY QTLs, qDTY1.1 and qDTY8.1 , which explained the PVEs of 11.61% to 12.88% and 15.79% to 18.77%, respectively. However, qDTY1.1 was found at the nearest position to the previously identified qDTYs. Through candidate gene analysis, the identified QTL regions in chromosome 1 (qDTY1.1) and chromosome 8 (qDTY8.1) revealed seven and five candidate genes, respectively, based on gene ontology that were significantly associated with rice grain yield-related drought traits. In conclusion, this study identified key consistent drought yield QTLs in a drought-tolerant exotic landrace. The identified QTLs provide valuable insights and resources for ongoing efforts to develop drought-tolerant rice varieties. They can be further utilized in drought breeding programs to enhance the drought resilience of existing varieties or to develop new varieties. [ABSTRACT FROM AUTHOR]

Leaf is the main photosynthetic organ at the seedling stage of rapeseed and leaf size is a crucial agronomic trait affecting rapeseed yield. Understanding the genetic mechanisms underlying leaf size is therefore important for rapeseed breeding. In this study, QTL mapping for three traits related to leaf size, i.e., leaf width (LW), leaf length (LL) and leaf area (LA), was performed using a recombinant inbred line (RIL) population and four QTLs for LW, two QTLs for LL and four QTLs for LA were detected. Transcriptome analysis revealed that differentially expressed genes (DEGs) were enriched in the GO terms related to microtubules, and the expression level of several genes involved in cell division also showed significant differences. Microscopic analysis suggested that the cell number was the main factor regulating leaf size. Combining QTL mapping and RNA sequencing, four promising candidate genes, including BnaA10G0085600ZS, BnaA10G0156900ZS, BnaC03G0441700ZS, and BnaC08G0410600ZS, were proposed to control leaf size by regulating cell division. The results of QTL, transcriptome analysis, and anatomical observation were highly consistent, collectively revealing that genes related to cell division played a crucial role in regulating the leaf size traits in rapeseed. These findings provided further insights into the genetic mechanism of leaf size and built fundamental theory basis for high-density tolerance breeding in rapeseed. [ABSTRACT FROM AUTHOR]

Zinc is an essential microelement of enzymes and proteins in wheat grains and humans. A deficiency in zinc content can lead to decreased wheat yield and low zinc content in grains, which in turn leads to insufficient dietary zinc intake. One recombinant inbred line (RIL) population derived from crosses Avocet/Huites (AH population) was used to map QTL for grain zinc content (GZnC) using diversity array technology (DArT). Nine QTLs were identified on chromosomes 2D, 3B, 4A, 4D, 5A, 5B, 6A, 7A, and 7D. Among them, QGZn.haust-AH-2D was detected in multiple environments, accounting for 5.61% to 11.27% of the phenotypic variation with a physical interval of 13.62 Mb to 17.82 Mb. Meanwhile, a genome-wide association study (GWAS) (CH population) comprising 243 cultivars or advanced lines revealed some genetic loci associated with zinc content in the wheat 660K single-nucleotide polymorphism (SNP) array. This was also identified within the physical interval of 13.61 Mb to 15.12 Mb of chromosome 2D, which accounted for 8.99% to 11.58% of the phenotypic variation in five models. A high-throughput competitive allele specific PCR (KASP) marker was developed, which verified the wheat natural population (NA population). QGZn.haust-AH-2D was fine mapped into a narrow region named TaZn-2DS between KAZn-2D-3 and 1111273 at a physical distance of 2.70 Mb, and the genetic effect of TaZn-2DS was 11.43%. This study shows that TaZn-2DS is associated with zinc content, and develops KAZn-2D-3 markers for the genetic improvement of nutritional quality in wheat. [ABSTRACT FROM AUTHOR]

Summary: DNA methylation is an essential epigenetic modification for gene regulation in plant growth and development. However, the precise mechanisms of DNA methylation remain poorly understood, especially in woody plants.We employed whole‐genome bisulfite sequencing (WGBS), assays for transposase‐accessible chromatin using sequencing (ATAC‐seq), and RNA‐Seq to investigate epigenetic regulatory relationships in Populus tomentosa treated with DNA methylation inhibitor 5‐azacitidine. Expression‐quantitative trait methylation analysis (eQTM), epigenome‐wide association study (EWAS), and joint linkage‐linkage disequilibrium mapping were used to explore the epigenetic regulatory genes, and using CRISPR/Cas9 to identify the role of candidate genes.Plant developmental abnormalities occurred when DNA methylation levels were substantially reduced. DNA methylation regulated 112 expressed genes via chromatin accessibility, of which 61 genes were significantly influenced by DNA methylation variation at the population level. One DNA methylation‐regulated gene, PtoGntK, was located in a major quantitative trait locus (QTL) for poplar growth. Overexpression and CRISPR/Cas9 of PtoGntK revealed it affected poplar height and stem diameter. The PtoRAP2.12 was found to bind to the demethylated accessible region in the PtoGntK promoter, thereby promoting growth in poplar.This study identified key genes with epigenetic regulation for plant growth and provides insights into epigenetic regulation mechanisms in woody plants. [ABSTRACT FROM AUTHOR]

Tofu is a popular soybean (Glycine max (L.) Merr.) food with a long tradition in Asia and rising popularity worldwide, including Central Europe. Due to the labour-intensive phenotyping procedures, breeding for improved tofu quality is challenging. Therefore, our objective was to unravel the genetic architecture of traits relevant for tofu production in order to assess the potential of marker-assisted selection and genomic selection in breeding for these traits. To this end, we performed QTL mapping with 188 genotypes from a biparental mapping population. The population was evaluated in a two-location field trial, and tofu was produced in the laboratory to evaluate tofu quality. We identified QTL for all investigated agronomic and quality traits, each explaining between 6.40% and 27.55% of the genotypic variation, including the most important tofu quality traits, tofu yield and tofu hardness. Both traits showed a strong negative correlation (r = -0.65), and consequently a pleiotropic QTL on chromosome 10 was found with opposite effects on tofu hardness and tofu weight, highlighting the need to balance selection for both traits. Four QTL identified for tofu hardness jointly explained 68.7% of the genotypic variation and are possible targets for QTL stacking by marker-assisted selection. To exploit also small-effect QTL, genomic selection revealed moderate to high mean prediction accuracies for all traits, ranging from 0.47 to 0.78. In conclusion, inheritance of tofu quality traits is highly quantitative, and both marker-assisted selection and genomic selection present valuable tools to advance tofu quality by soybean breeding. [ABSTRACT FROM AUTHOR]

Copyright of Acta Agronomica Sinica is the property of Crop Science Society of China and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Yield-related traits have higher heritability and lower genotype-by-environment interaction, making them more suitable for genetic studies in comparison with the yield per se. Different populations have been developed and employed in QTL mapping; however, the use of reciprocal SSSLs is limited. In this study, three kinds of bi-parental populations were used to investigate the stable and novel QTLs on six yield-related traits, i.e., plant height (PH), heading date (HD), thousand-grain weight (TGW), effective tiller number (ETN), number of spikelets per panicle (NSP), and seed set percentage (SS). Two parental lines, i.e., japonica Asominori and indica IR24, their recombinant inbred lines (RILs), and reciprocal single-segment substitution lines (SSSLs), i.e., AIS and IAS, were genotyped by SSR markers and phenotyped in four environments with two replications. Broad-sense heritability of the six traits ranged from 0.67 to 0.94, indicating their suitability for QTL mapping. In the RIL population, 18 stable QTLs were identified for the six traits, 4 for PH, 6 for HD, 5 for TGW, and 1 each for ETN, NSP, and SS. Eight of them were validated by the AIS and IAS populations. The results indicated that the allele from IR24 increased PH, and the alternative allele from Asominori reduced PH at qPH3-1. AIS18, AIS19, and AIS20 were identified to be the donor parents which can be used to increase PH in japonica rice; on the other hand, IAS14 and IAS15 can be used to reduce PH in indica rice. The allele from IR24 delayed HD, and the alternative allele reduced HD at qHD3-1. AIS14 and AIS15 were identified to be the donor parents which can be used to delay HD in japonica rice; IAS13 and IAS14 can be used to reduce HD in indica rice. Reciprocal SSSLs not only are the ideal genetic materials for QTL validation, but also provide the opportunity for fine mapping and gene cloning of the validated QTLs. [ABSTRACT FROM AUTHOR]

Wheat, a major cereal crop, is the most consumed staple food after rice in India. Frequent episodes of heat waves during the past decade have raised concerns about food security under impending global warming and necessitate the development of heat-tolerant wheat cultivars. Wild relatives of crop plants serve as untapped reservoirs of novel genetic variations. In the present study a mapping population comprising 311 BC2F10 backcross introgression lines (BILs) developed by crossing Triticum durum and heat-tolerant diploid wild wheat relative Aegilops speltoides accession pau3809 was used to map QTLs for terminal heat tolerance. The homozygous BILs were evaluated for heat stress tolerance component traits under an optimum environment (OE) and a heat-stressed environment (HE) for the two cropping seasons. Data on spike length, spikelet number per spike, peduncle length, thousand-grain weight, grains per spike, days to heading, days to maturity, grain filling duration, NDVI at heading, plant height and plot yield were recorded. Genotyping-by-sequencing (GBS) of the BILs was carried out, and 2945 high-quality, polymorphic SNPs were obtained. Thirty QTLs were detected for various heat tolerance component traits on chromosomes 1A, IB, 2A, 2B, 3B, 4B, 5A, 5B, 6A and 6B with phenotypic variance ranging from 5 to 11.5%. Several candidate genes reported to play a role in heat stress responses were identified by browsing the 1.85 Mb physical region flanking the stable QTLs detected under the HE. Identified QTL and linked markers can be employed for genomics-assisted breeding for heat tolerance in wheat. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Owing to advances in high-throughput genome sequencing, QTL-Seq mapping of salt tolerance traits is a major platform for identifying soil-salinity tolerance QTLs to accelerate marker-assisted selection for salt-tolerant rice varieties. We performed QTL-BSA-Seq in the seedling stage of rice from a genetic cross of the extreme salt-sensitive variety, IR29, and Jao Khao (JK), a Thai salt-tolerant variety. METHODS: A total of 462 F2 progeny grown in soil and treated with 160 mM NaCl were used as the QTL mapping population. Two high- and low-bulk sets, based on cell membrane stability (CMS) and tiller number at the recovery stage (TN), were equally sampled. The genomes of each pool were sequenced, and statistical significance of QTL was calculated using QTLseq and G prime (G) analysis, which is based on calculating the allele frequency differences or Δ(SNP index). RESULTS: Both methods detected the overlapping interval region, wherein CMS-bulk was mapped at two loci in the 38.41-38.85 Mb region with 336 SNPs on chromosome 1 (qCMS1) and the 26.13-26.80 Mb region with 1,011 SNPs on chromosome 3 (qCMS3); the Δ(SNP index) peaks were -0.2709 and 0.3127, respectively. TN-bulk was mapped at only one locus in the overlapping 38.26-38.95 Mb region on chromosome 1 with 575 SNPs (qTN1) and a Δ(SNP index) peak of -0.3544. These identified QTLs in two different genetic backgrounds of segregating populations derived from JK were validated. The results confirmed the colocalization of the qCMS1 and qTN1 traits on chromosome 1. Based on the CMS trait, qCMS1/qTN1 stably expressed 6%-18% of the phenotypic variance in the two validation populations, while qCMS1/qTN1 accounted for 16%-20% of the phenotypic variance in one validation population based on the TN trait. CONCLUSION: The findings confirm that the CMS and TN traits are tightly linked to the long arm of chromosome 1 rather than to chromosome 3. The validated qCMS-TN1 QTL can be used for gene/QTL pyramiding in marker-assisted selection to expedite breeding for salt resistance in rice at the seedling stage.

Pod quality and yield traits in snap bean (Phaseolus vulgaris L.) influence consumer preferences, crop adoption by farmers, and the ability of the product to be commercially competitive locally and globally. The objective of the study was to identify the quantitative trait loci (QTL) for pod quality and yield traits in a snap × dry bean recombinant inbred line (RIL) population. A total of 184 F6 RILs derived from a cross between Vanilla (snap bean) and MCM5001 (dry bean) were grown in three field sites in Kenya and one greenhouse environment in Davis, CA, USA. They were genotyped at 5,951 single nucleotide polymorphisms (SNPs), and composite interval mapping was conducted to identify QTL for 16 pod quality and yield traits, including pod wall fiber, pod string, pod size, and harvest metrics. A combined total of 44 QTL were identified in field and greenhouse trials. The QTL for pod quality were identified on chromosomes Pv01, Pv02, Pv03, Pv04, Pv06, and Pv07, and for pod yield were identified on Pv08. Co-localization of QTL was observed for pod quality and yield traits. Some identified QTL overlapped with previously mapped QTL for pod quality and yield traits, with several others identified as novel. The identified QTL can be used in future marker-assisted selection in snap bean.

Abstract Background Peanut (Arachis hypogaea L.) is a globally important oilseed and cash crop. Web blotch is one of the most important peanut foliar diseases, causing severe yield losses worldwide. Results In this study, an F6 population was used to identify quantitative trait loci (QTLs) for peanut web blotch resistance, based on bulked segregant analysis (BSA). Kompetitive Allele-Specific PCR (KASP) markers were developed and used to further narrow QTL intervals and detect candidate genes. Two major QTLs, qWBRA05 and qWBRA08 were identified, spanning physical intervals of 465.75 Kb and 434.83 Kb, and explaining percentages of phenotypic variation (PVE) of 8.79% and 15.09%, respectively. Moreover, two KASP markers were developed within the QTL interval effectively distinguished between web blotch resistance and web blotch susceptible materials. Conclusions The QTLs identified and two molecular markers closely linked to web blotch resistance were developed within the QTL interval, which are potentially valuable in peanut breeding.

Abstract Fruit diameter is one of important agronomy traits that has greatly impacts fruit yield and commercial value in cucumber (Cucumis sativus L.). Hence, we preliminary mapping of fruit diameter was conducted to refine its genetic locus. In this study, to genetic mapping of QTLs that control cucumber fruit diameter, a F2 population with 120 individuals was developed by the East Asian line ‘9930’ (known as narrow fruit diameter) and the European-type cucumber ‘EU224’ (known as wide fruit diameter). Then a Genotyping-by-Sequencing (GBS)-based genetic map with 5662 markers was constructed and the total length is 656.177 cM, with average marker interval of 0.116 cM. Based on this high-density genetic map, a major QTL qfd1.1 related to fruit diameter was detected with a markedly high LOD score 4.07 located approximately 300 kb interval on Chromosome 1 (located between Chr1:1654704–1958556). To confirm qfd1.1 that detected by F2 population, we performed genetic mapping of fruit diameter with an introgression line (IL) about fruit diameter. We developed two KASP markers (FD-1 and FD-2) related to the fruit diameter. Based on this, we inserted the European cucumber EU224 into the qfd1.1 range and targeted widening the fruit diameter of the 9930 cucumber variety, further indicating that qfd1.1 is a new locus regulating the fruit diameter of cucumber. Our findings will support breeders in their research on cucumber fruit diameter.

【Objective】High-temperature and rainy weather lead to pre-harvest sprouting (PHS), severely impacting yield and quality traits of rice. Identification and screening of germplasm or genetic resources is a fundamental pathway for developing new varieties resistant to PHS and eliminating PHS damage.【Method】In the study, a set of chromosome segment substitution lines (CSSLs) derived from Dongxiang wild rice ('C35') as the donor parent and 'Nipponbare' ('NIP') as the recipient parent were used as the experimental materials, and then PHS resistance were evaluated and QTLs were mapped in 2021-2023, with an aim to screen PHS germplasm and identify major QTLs.【Result】Dongxiang wild rice 'C35' exhibited strong dormancy under different environments with a pre-harvest sprouting rate (PHSR) of 0.00%; 'Nipponbare' showed significant PHS with an average PHSR of 31.95%. The PHSR varied widely among CSSL populations, the phenotypic repeatability of PHSR was relatively high in different years, and ten lines from the CSSL populations with strong dormancy and resistance to PHS were screened. A total of 14 QTLs controlling the PHSR were detected, and four QTLs were repeatedly detected under different environments. These QTLs formed four QTL clusters (qPHSRC1, qPHSRC2, qPHSRC8 and qPHSRC9), among which qPHSRC2 and qPHSRC9 had higher LOD values, phenotypic contribution rate (%) and additive effect, and qPHSRC2 was a newly discovered major QTL cluster.【Conclusion】A batch of PHS resistant germplasms were screened and 14 QTLs were mapped, four QTL clusters were repeatedly identified, and a new major QTL cluster qPHSRC2 controlling the PHSR was discovered.

Abstract Background In this study, tropical maize germplasms were used to construct a multiparent population (MPP) to identify novel genes associated with kernel protein content. The kernel protein content was quantified using near-infrared spectroscopy (NIRS) in the MPP, which was evaluated in three different environments. Results QTL mapping revealed 23 significant QTLs tightly linked to kernel protein content, with phenotypic variation ranging from 8.88 to 28.86%. Genome-wide association analysis (GWAS) identified 21 SNPs that were significantly associated with kernel protein content, with phenotypic variation explained (PVE) ranging from 4.09 to 16.15%. Through combined QTL mapping and GWAS, co-localized loci were identified, as well as two novel genes (Zm00001d034933 and Zm00001d029999) that had not been previously reported. Conclusions These genes encode pentatricopeptide repeat-containing proteins (PPR proteins), which regulate kernel endosperm development. The significant SNPs associated with these genes accounted for 23.59% of the PVE, whereas the QTLs accounted for 46.02% of the phenotypic variation. Since kernel protein synthesis and storage occur in the endosperm, this study suggests that Zm00001d034933 and Zm00001d029999 may potentially regulate kernel protein content in maize.

Seed size is an important agronomic trait in melons that directly affects seed germination and subsequent seedling growth. However, the genetic mechanism underlying seed size in melon remains unclear. In the present study, we employed Bulked-Segregant Analysis sequencing (BSA-seq) to identify a candidate region (~1.35 Mb) on chromosome 6 that corresponds to seed size. This interval was confirmed by QTL mapping of three seed size-related traits from an F2 population across three environments. This mapping region represented nine QTLs that shared an overlapping region on chromosome 6, collectively referred to as qSS6.1. New InDel markers were developed in the qSS6.1 region, narrowing it down to a 68.35 kb interval that contains eight annotated genes. Sequence variation analysis of the eight genes identified a SNP with a C to T transition mutation in the promoter region of MELO3C014002, a leucine-rich repeat receptor-like kinase (LRR-RLK) gene. This mutation affected the promoter activity of the MELO3C014002 gene and was successfully used to differentiate the large-seeded accessions (C-allele) from the small-seeded accessions (T-allele). qRT-PCR revealed differential expression of MELO3C014002 between the two parental lines. Its predicted protein has typical LRR-RLK family domains, and phylogenetic analyses reveled its similarity with the homologs in several plant species. Altogether, these findings suggest MELO3C014002 as the most likely candidate gene involved in melon seed size regulation. Our results will be helpful for better understanding the genetic mechanism regulating seed size in melons and for genetically improving this important trait through molecular breeding pathways.

Cotton breeding for the development of early-maturing varieties is an effective way to improve multiple cropping indexes and alleviate the conflict between grains and cotton in the cultivated fields in China. In the present study, we aimed to identify upland cotton quantitative trait loci (QTLs) and candidate genes related to early-maturity traits, including whole growth period (WGP), flowering timing (FT), node of the first fruiting branch (NFFB), height of the node of the first fruiting branch (HNFFB), and plant height (PH). An early-maturing variety, CCRI50, and a late-maturing variety, Guoxinmian 11, were crossed to obtain biparental populations. These populations were used to map QTLs for the early-maturity traits for two years (2020 and 2021). With BSA-seq analysis based on the data of population 2020, the candidate regions related to early maturity were found to be located on chromosome D03. We then developed 22 polymorphic insertions or deletions (InDel) markers to further narrow down the candidate regions, resulting in the detection of five and four QTLs in the 2020 and 2021 populations, respectively. According to the results of QTL mapping, two candidate regions (InDel_G286-InDel_G144 and InDel_G24-InDel_G43) were detected. In these regions, three genes (GH_D03G0451, GH_D03G0649, and GH_D03G1180) have non-synonymous mutations in their exons and one gene (GH_D03G0450) has SNP variations in the upstream sequence between CCRI50 and Guoxinmian 11. These four genes also showed dominant expression in the floral organs. The expression levels of GH_D03G0451, GH_D03G0649 and GH_D03G1180 were significantly higher in CCRI50 than in Guoxinmian 11 during the bud differentiation stages, while GH_D03G0450 showed the opposite trend. Further functional verification of GH_D03G0451 indicated that the GH_D03G0451-silenced plants showed a delay in the flowering time. The results suggest that these are the candidate genes for cotton early maturity, and they may be used for breeding early-maturity cotton varieties.

Wheat domestication and subsequent genetic improvement have yielded cultivated species with larger seeds compared to wild ancestors. Increasing thousand kernel weight (TKW) remains a crucial goal in many wheat breeding programs. To identify genomic regions influencing TKW across diverse genetic populations, we performed a comprehensive meta-analysis of quantitative trait loci (MQTL), integrating 993 initial QTL from 120 independent mapping studies over recent decades. We refined 242 loci into 66 MQTL, with an average confidence interval (CI) 3.06 times smaller than that of the original QTL. In these 66 MQTL regions, a total of 4,913 candidate genes related to TKW were identified, involved in ubiquitination, phytohormones, G-proteins, photosynthesis, and microRNAs. Expression analysis of the candidate genes showed that 95 were specific to grain and might potentially affect TKW at different seed development stages. These findings enhance our understanding of the genetic factors associated with TKW in wheat, providing reliable MQTL and potential candidate genes for genetic improvement of this trait. [ABSTRACT FROM AUTHOR]

Summary Pollination syndromes are a key component of flowering plant diversification, prompting questions about the architecture of single traits and genetic coordination among traits. Here, we investigate the genetics of extreme floral divergence between naturally hybridizing monkeyflowers, Mimulus parishii (self‐pollinated) and M. cardinalis (hummingbird‐pollinated). We mapped quantitative trait loci (QTLs) for 18 pigment, pollinator reward/handling, and dimensional traits in parallel sets of F2 hybrids plus recombinant inbred lines and generated nearly isogenic lines (NILs) for two dimensional traits, pistil length and corolla size. Our multi‐population approach revealed a highly polygenic basis (n = 190 QTLs total) for pollination syndrome divergence, capturing minor QTLs even for pigment traits with leading major loci. There was significant QTL overlap within pigment and dimensional categories. Nectar volume QTLs clustered with those for floral dimensions, suggesting a partially shared module. The NILs refined two pistil length QTLs, only one of which has tightly correlated effects on other dimensional traits. An overall polygenic architecture of floral divergence is partially coordinated by genetic modules formed by linkage (pigments) and likely pleiotropy (dimensions plus nectar). This work illuminates pollinator syndrome diversification in a model radiation and generates a robust framework for molecular and ecological genomics. [ABSTRACT FROM AUTHOR]

Background: Peanut (Arachis hypogaea L.) is a globally important oilseed and cash crop. Web blotch is one of the most important peanut foliar diseases, causing severe yield losses worldwide. Results: In this study, an F6 population was used to identify quantitative trait loci (QTLs) for peanut web blotch resistance, based on bulked segregant analysis (BSA). Kompetitive Allele-Specific PCR (KASP) markers were developed and used to further narrow QTL intervals and detect candidate genes. Two major QTLs, qWBRA05 and qWBRA08 were identified, spanning physical intervals of 465.75 Kb and 434.83 Kb, and explaining percentages of phenotypic variation (PVE) of 8.79% and 15.09%, respectively. Moreover, two KASP markers were developed within the QTL interval effectively distinguished between web blotch resistance and web blotch susceptible materials. Conclusions: The QTLs identified and two molecular markers closely linked to web blotch resistance were developed within the QTL interval, which are potentially valuable in peanut breeding. [ABSTRACT FROM AUTHOR]

Uppermost internode length (UIL) and panicle exsertion are two important traits that contribute significantly to increased yield in rice. The present study was conducted using recombinant inbred lines (RILs) comprising 201 lines derived from RTN10B and IRG213. These RILs were evaluated at three different locations— Delhi, Karnal, and Aduthurai. We report the mapping of quantitative trait loci (QTLs) for uppermost internode length and the panicle exsertion ratio (PER), as well as QTLs for plant height (PH), tiller number, length of the second internode, length of the third internode, length from the flag leaf to the panicle tip (PFL), and panicle length (PL). Mapping was performed using a custom microsatellite linkage map constructed for the population, having a total span of 2077.1 cM with 104 markers. A total of 22 QTLs were identified for various traits, among which 19 were found distributed in four hotspots. A total of 11 major effect QTLs and 11 minor effect QTLs were identified for various internode length-related traits. Among the four QTLs identified for PFL, three QTLs— qPFL1.1 , qPFL1.2, and qPFL2.1 —co-localized with previously reported QTLs, while qPFL8.1 was a novel QTL. A major QTL hotspot was identified on chromosome 1, located at the marker interval of RM12055-RM320. The size of the major QTL hotspot on chromosome 1 was 1.4 Mb and contained a total of seven HEs for PER, PFL, PH, PL, UIL, SIL, and TIL. Based on the in-silico analysis of the major QTL hotspot on chromosome 1, we identified 15 putative candidate genes associated with internode length- and panicle-related traits. Furthermore, narrowing the genomic region through the fine mapping of the marker intervals facilitated the identification of candidate genes to enable more precise marker-assisted selection for uppermost internode length and panicle exsertion. [ABSTRACT FROM AUTHOR]

The genetic mechanisms underlying striking axial patterning changes in wild species are still largely unknown. Previous studies have shown that Apeltes quadracus fish, commonly known as fourspine sticklebacks, have evolved multiple different axial patterns in wild populations. Here, we revisit classic locations in Nova Scotia, Canada, where both high-spined and low-spined morphs are particularly common. Using genetic crosses and quantitative trait locus (QTL) mapping, we examine the genetic architecture of wild differences in several axial patterning traits, including the number and length of prominent dorsal spines, the number of underlying median support bones (pterygiophores), and the number and ratio of abdominal and caudal vertebrae along the anterior–posterior body axis. Our studies identify a highly significant QTL on chromosome 6 that controls a substantial fraction of phenotypic variation in multiple dorsal spine and pterygiophore traits (~15%–30% variance explained). An additional smaller-effect QTL on chromosome 14 contributes to the lengths of both the last dorsal spine and anal spine (~9% variance explained). 1 or no QTL were detected for differences in the numbers of abdominal and caudal vertebrae. The major-effect patterning QTL on chromosome 6 is centered on the HOXDB gene cluster, where sequence changes in a noncoding axial regulatory enhancer have previously been associated with prominent dorsal spine differences in Apeltes. The QTL that have the largest effects on dorsal spine number and length traits map to different chromosomes in Apeltes and Gasterosteus , 2 distantly related stickleback genera. However, in both genera, the major-effect QTL for prominent skeletal changes in wild populations maps to linked clusters of powerful developmental control genes. This study, therefore, bolsters the body of evidence that regulatory changes in developmental gene clusters provide a common genetic mechanism for evolving major morphological changes in natural species. [ABSTRACT FROM AUTHOR]

Rice sheath blight is one of the most important fungal disease‐causing yield losses up to 50%. An Oryza rufipogon‐derived introgression line (Pusa 1908‐13‐12‐5) identified to be highly resistant to sheath blight was used for developing a RIL population by crossing with a highly susceptible rice cultivar, Pusa Basmati 1 (PB 1). The RIL population was genotyped with 80K Rice Pangenome (RPAN) single nucleotide polymorphism (SNP) array and phenotyped for disease response under artificial inoculation for 2 consecutive years. Inclusive composite interval mapping could identify six quantitative trait loci (QTLs) for two traits, namely, relative lesion height and relative yield loss per plant. Among these QTLs, four were major QTLs and three are novel QTLs. Three major QTLs were co‐localised within 1.4 Mb region on chromosome 1. In silico analysis revealed the presence of 12 candidate genes with potential role in disease resistance. Kompetitive Allele Specific PCR (KASP™) assay was developed for the linked SNPs and used for validation in an independent BC1F2:3 population (PB 1121/Pusa 1908‐13‐12‐5). One SNP (AX‐182186537) on chromosome 1 was validated, which offers scope for its utilisation in marker‐assisted breeding. [ABSTRACT FROM AUTHOR]

Branching number (BN) is a crucial architectural trait in Cucumis melo. Because of its multiple branch habits, much more labour costs are needed in melon production. However, the genetic mechanism of branching numbers in melon is not clear. Here, a genetic population from multiple branching material S8 (only two branching number in the first node) as the female line and S7 (multiple branching numbers in each node; more than nine branch numbers) as the male parent is used to make a cross F2:3 generation. By performing QTL mapping based on bulked segregate analysis (BSA) after two years, a candidate QTL region of the BN was located on chromosome 3. For further QTL mapping, a genetic linkage map, which contained 16 SSR markers with a total length of 2.27 Mb, was constructed. One major QTL locus bnDQ-2022-3.1 was detected between CmSSR9556 and CmSSR9580, with a LOD threshold of 11.37 and a contribution rate of 49.11% in the spring of 2022 in Daqing City. Then, a consistent QTL bnSY-2022-3.1 was also investigated in Sanya, Hainan Province, in the autumn of 2022, with a LOD threshold of 10.85 and a contribution rate of 45.01%. Nine genes were investigated within the interval of the candidate region located in chromosome 3 between 22,723,436 and 22,807,889 of the melon's physical position within the 85.45 kb length region. Gene expression analysis showed significant differences between MELO3C019872.2.1, MELO3C030060.2.1, and MELO3C019871.2.1 in different development stages. Gene sequence different analysis revealed a "C"-to-"T" mutation in the 1280 bp site of MELO3C030060.2.1 in parental lines. Heterologous transformation of MELO3C030060.2.1 into cucumber revealed that overexpression of MELO3C030060.2.1 resulted in more and denser branches in cucumber plants, and the growth rate of lateral branches was significantly faster than that of the wild type. Transferring to antisense of MELO3C030060.2.1 had the opposite effect. To sum up, MELO3C030060.2.1 is related to melon branching initial habits. This study could provide a new insight into melon branching habits and provide a theoretical base for melon breeding. [ABSTRACT FROM AUTHOR]

In modern plant breeding, molecular markers have become indispensable tools, allowing the precise identification of genetic loci linked to key agronomic traits. These markers provide critical insight into the genetic architecture of crops, accelerating the selection of desirable traits for sustainable agriculture. This review focuses on the advancements in quantitative trait locus (QTL) mapping and genome-wide association studies (GWASs), highlighting their effective roles in identifying complex traits such as stress tolerance, yield, disease resistance, and nutrient efficiency. QTL mapping identifies the significant genetic regions linked to desired traits, while GWASs enhance precision using larger populations. The integration of high-throughput phenotyping has further improved the efficiency and accuracy of QTL research and GWASs, enabling precise trait analysis across diverse conditions. Additionally, next-generation sequencing, clustered regularly interspaced short palindromic repeats (CRISPR) technology, and transcriptomics have transformed these methods, offering profound insights into gene function and regulation. Single-cell RNA sequencing further enhances our understanding of plant responses at the cellular level, especially under environmental stress. Despite this progress, however, challenges persist in optimizing methods, refining training populations, and integrating these tools into breeding programs. Future studies must aim to enhance genetic prediction models, incorporate advanced molecular technologies, and refine functional markers to tackle the challenges of sustainable agriculture. [ABSTRACT FROM AUTHOR]

Key message: The QTLs and candidate genes governing the multifoliolate phenotype were identified by combining linkage mapping with BSR-seq, revealing a possible interplay between genetics and the environment in soybean leaf development. Soybean, as a legume, is typified by trifoliolate leaves. Although multifoliolate leaves (compound leaves with more than three leaflets each) have been reported in soybean, including sporadic appearances in the first compound leaves in a recombinant inbred line (RIL) population from a cross between cultivated soybean C08 and wild soybean W05 from this study, the genetic basis of this phenomenon is still unclear. Here, we integrated quantitative trait locus (QTL) mapping with bulked segregant RNA sequencing (BSR-seq) to identify the genetic loci associated with the multifoliolate phenotype in soybean. Using linkage mapping, ten QTLs related to the multifoliolate trait were identified. Among these, a significant and major QTL, qMF-2-1 on chromosome 2 and consistently detected across biological replicates, explained more than 10% of the phenotypic variation. Together with BSR-seq analyses, which analyzed the RILs with the highest multifoliolate frequencies and those with the lowest frequencies as two distinct bulks, two candidate genes were identified: Glyma.06G204300 encoding the transcription factor TCP5, and Glyma.06G204400 encoding LONGIFOLIA 2 (LNG2). Transcriptome analyses revealed that stress-responsive genes were significantly differentially expressed between high-multifoliolate occurrence lines and low occurrence ones, indicating environmental factors probably influence the appearance of multifoliolate leaves in soybean through stress-responsive genes. Hence, this study offers new insights into the genetic mechanism behind the multifoliolate phenotype in soybean. [ABSTRACT FROM AUTHOR]

Kernel row number (KRN) is one of the key traits that significantly affect maize yield and productivity. Therefore, investigating the candidate genes and their functions in regulating KRN provides a theoretical basis and practical direction for genetic improvement in maize breeding, which is vital for increasing maize yield and understanding domestication. In this study, three recombinant inbred line (RIL) populations were developed using the parental lines AN20, YML1218, CM395, and Ye107, resulting in a multiparent population comprising a total of 490 F9 RILs. Phenotypic evaluation of the RILs for KRN was performed in three distinct environments. The heritability estimates of the RILs ranged from 81.40% to 84.16%. Genotyping-by-sequencing (GBS) of RILs identified 569,529 high-quality single nucleotide polymorphisms (SNPs). Combined genome-wide association study (GWAS) and linkage analyses revealed 120 SNPs and 22 quantitative trait loci (QTLs) which were significantly associated with KRN in maize. Furthermore, two novel candidate genes, Zm00001d042733 and Zm00001d042735, regulating KRN in maize were identified, which were located in close proximity to the significant SNP3-178,487,003 and overlapping the interval of QTL qKRN3-1. Zm00001d042733 encodes ubiquitin carboxyl-terminal hydrolase and Zm00001d042735 encodes the Arabidopsis Tóxicos en Levadura family of proteins. This study identified novel candidate loci and established a theoretical foundation for further functional validation of candidate genes. These findings deepen our comprehension of the genetic mechanisms that underpin KRN and offer potential applications of KRN-related strategies in developing maize varieties with higher yield. [ABSTRACT FROM AUTHOR]

Background: In this study, tropical maize germplasms were used to construct a multiparent population (MPP) to identify novel genes associated with kernel protein content. The kernel protein content was quantified using near-infrared spectroscopy (NIRS) in the MPP, which was evaluated in three different environments. Results: QTL mapping revealed 23 significant QTLs tightly linked to kernel protein content, with phenotypic variation ranging from 8.88 to 28.86%. Genome-wide association analysis (GWAS) identified 21 SNPs that were significantly associated with kernel protein content, with phenotypic variation explained (PVE) ranging from 4.09 to 16.15%. Through combined QTL mapping and GWAS, co-localized loci were identified, as well as two novel genes (Zm00001d034933 and Zm00001d029999) that had not been previously reported. Conclusions: These genes encode pentatricopeptide repeat-containing proteins (PPR proteins), which regulate kernel endosperm development. The significant SNPs associated with these genes accounted for 23.59% of the PVE, whereas the QTLs accounted for 46.02% of the phenotypic variation. Since kernel protein synthesis and storage occur in the endosperm, this study suggests that Zm00001d034933 and Zm00001d029999 may potentially regulate kernel protein content in maize. [ABSTRACT FROM AUTHOR]

Sesame (Sesamum indicum L.) is an important oilseed crop widely cultivated in subtropical and tropical areas. Low genetic yield potential and susceptibility to disease contribute to low productivity in sesame. However, the genetic basis of sesame yield- and disease-related traits remains unclear. Here, we represent the construction of a high-density bin map of sesame using whole genome sequencing of an F2 population derived from 'Yizhi' and 'Mingdeng Zhima'. A total of 2766 Bins were categorized into 13 linkage groups. Thirteen significant QTLs were identified, including ten QTLs related to yield, two QTLs related to Sesame Fusarium wilt (SFW) disease, and one QTL related to seed color. Among these QTLs, we found that SFW-QTL1.1 and SFW-QTL1.2 were major QTLs related to Fusarium wilt disease, explaining more than 20% of the phenotypic variation with LOD > 6. SCC-QTL1.1 was related to seed coat color, explaining 52% of the phenotypic variation with LOD equal to 25.3. This suggests that seed color traits were controlled by a major QTL. Candidate genes related to Fusarium wilt disease and seed color in the QTLs were annotated. We discovered a significant enrichment of genes associated with resistance to late blight. These genes could be spectral disease resistance genes and may have a role in the regulation of Fusarium wilt disease resistance. Our study will benefit the implementation of marker-assisted selection (MAS) for the genetic improvement of disease resistance and yield-related traits in sesame. [ABSTRACT FROM AUTHOR]

Water-soluble protein is an important component of soybean seeds and is usually used as an indicator of soybean quality, especially in soybean food processing. Compared with studies on seed protein or oil content, genetic studies on water-soluble protein content (WSPC) in soybean have lagged. Therefore, to identify genes associated with WSPC in soybean seeds, we systematically performed a quantitative trait locus (QTL) mapping study based on a recombinant inbred line population consisting of 237 lines derived from Zheng 92116 and Williams 82 and SNP or InDel markers from a genotyping-by-sequencing protocol. As a result, the WSPC at 3 locations from 2016 to 2017 ranged from 26.69 to 40.35% and was normally distributed in each environment. A genetic map consisting of 6,597 markers distributed in 20 linkage groups was constructed. By using the iciMapping and QTL.gCIMapping programs, a total of 20 QTLs with a PVE (proportion of phenotypic variance explained) ranging from 1.86 to 30.03%, distributed throughout 9 chromosomes, were detected, including 2 major QTLs. Among the 20 QTLs, 9 were stable; these QTLs were detected by both programs and/or in two or more datasets and usually presented relatively high LOD and PVE values. Compared with previous studies, 8 of the 20 QTLs above were newly identified, and the other 12 QTLs were the same or identical to the WSPC QTLs reported previously. To identify potential genes underlying WSPC, the QTL with the largest effect, i.e., qWSPC5-3, was selected for further analysis on the basis of the RNA-seq datasets, and the expression profiles of the 27 genes within this interval were analyzed. These results shed new light on the genetics of WSPC in soybean and may also provide important information for improving the functional quality of soybean varieties for breeders. [ABSTRACT FROM AUTHOR]

Pre-harvest sprouting (PHS) is a serious threat to wheat quality and occurs when maturing seeds on plants encounter substantial rain before harvest. In the present study, the genetics of PHS resistance were studied using a population of 131 recombinant inbred lines (RILs) from a cross between Soru#1 and Naxos. The population was genotyped with the Illumina 90 K and Axiom 35 K wheat SNP arrays and tested in field trials across two locations in Norway and one in China. Seed dormancy as a measure of sprouting damage was evaluated using germination index (GI) and falling number (FN). Days to heading, days to maturity, and plant height were also recorded to evaluate their potential impact on PHS. Thirteen PHS-related quantitative trait loci (QTL) were detected. The most consistent QTL for FN, contributed by Soru#1, on the long arm of chromosome 4B explained 10.0–19.2% of the phenotypic variation across trials. Other important PHS resistance QTL from Soru#1 detected on chromosome arms 2AL, 2BL, and 4BS, affected both GI and FN. Naxos carried favorable QTL alleles for PHS resistance on chromosome arm 4AS and the Phs1 allele on 4AL. The reduced height Rht-D1 and vernalization Vrn-A1 alleles were the major determinants of plant height and earliness; however, these traits had minimal impact on the genetic control of PHS resistance in this population. Thus, both parents contributed valuable alleles for improving PHS resistance in breeding programs. [ABSTRACT FROM AUTHOR]

Durum wheat (Triticum turgidum) is threatened by the appearance of new virulent races of leaf rust, caused by Puccinia triticina, in recent years. This study was conducted to determine the leaf rust resistance in a modern Canadian durum cultivar, Strongfield. Six populations derived from crosses of Strongfield with six tetraploid wheat lines, respectively, were tested at the seedling plant stage with different P. triticina races. Two of the populations were evaluated for adult plant leaf rust infection in Canada and Mexico. A stepwise regression joint linkage quantitative trait locus (QTL) mapping and analysis by MapQTL were performed. Strongfield contributed the majority of QTLs detected, contributing seven QTLs detected in field tests and eight QTLs conditioning seedling resistance. A 1B QTL, QLr-Spa-1B.1, from Strongfield had a significant effect in both Canadian and Mexican field tests and corresponded with Lr46/Yr29. The remaining field QTLs were found in only the Canadian or the Mexican environment, not both. The QTL from Strongfield on 3A, QLr-Spa-3A, conferred seedling resistance to all races tested and had a significant effect in the field in Canada. This is the first report of QLr-Spa-3A and Lr46/Yr29 as key components of genetic resistance in Canadian durum wheat. KASP markers were developed to detect QLr-Spa-3A for use in marker-assisted leaf rust resistance breeding. The susceptible parental lines contributed QTLs on 1A, 2B, and 5B that were effective in Mexican field tests and may be good targets to integrate into modern durum varieties to improve resistance to new durum virulent races. [ABSTRACT FROM AUTHOR]

Flesh firmness is an important quality of pear fruits. Breeding cultivars with suitably low flesh firmness is one of the popular pear breeding goals. At present, SNP markers related to pear flesh firmness and genes affecting flesh firmness are still uncertain. In this study, a QTL analysis was performed, and the result showed that the position of 139.857 cM in lineage group 14 (LG14) had the highest average logarithm of odds (3.41) over two years. This newly discovered locus was identified as a flesh firmness-related QTL (qFirmness-LG14). The 'C/T' SNP was found in corresponding Marker1512129. The 'C' genotype is the high-firmness genotype, which is a dominant trait. The average firmness of fruits with genotype C is 21.4% higher than genotype without the C genotype. Transcriptome profiling was obtained between 'Zaoshengxinshui' and 'Qiushui' at five time points. Three candidate genes in the interval of qFirmness-LG14 might affect firmness. A gene of xyloglucan endotransglucosylase 1 (PpXTH1) was upregulated in 'Qiushui' at all five time points. Two transcription factors (PpHY5 and PpERF113) were upregulated in 'Zaoshengxinshui', which might be negative regulatory genes for high flesh firmness. The transcriptome results also isolated a large number of cell wall-related genes (e.g., Pectate lyase, Pectin acetylesterase, Pectin methylesterase, and 4-coumarate-CoA ligase) and transcription factors (e.g., ERF, WRKY). These genes are all potential upstream and downstream genes related to flesh firmness. In conclusion, this study provides valuable insights into the QTLs and molecular mechanisms associated with fruit firmness in Pyrus pyrifolia. [ABSTRACT FROM AUTHOR]

Powdery mildew is a prevalent wheat disease that affects yield and quality. The characterization and fine mapping of genes associated with powdery mildew resistance can benefit marker-assisted breeding. In this study, quantitative trait loci (QTL) associated with powdery mildew were mapped using a high-density 35K DArT genetic linkage map developed from a population of double haploid lines (DHs) created by crossing "Jinmai 33 (a highly resistance line) with Yannong 19 (a highly susceptible line)". Three stable QTLs for powdery mildew were identified on chromosomes 1B, 2B, and 6A combined with the composite interval graphing method and multiple interval mapping, explaining phenotypic variations (PVE) that range from 4.98% to 13.25%. Notably, Qpm.sxn-1B and Qpm.sxn-2B were identified across three environments, with the PVE ranging from 9.37% to 13.25% and from 4.98% to 5.23%, respectively. The synergistic effects of these QTLs were contributed by the parental line "Jinmai 33". Qpm.sxn-1B was the major stable QTL, and Qpm.sxn-2B was close to Pm51. Furthermore, Qpm.sxn-6A was identified in two environments, accounting for PVE values of 7.13% and 7.65%, respectively, with the resistance effects originating from the male parent. Remarkably, this locus has not been reported previously, indicating that Qpm.sxn-6A represents a newly dis-covered QTL governing powdery mildew genes. Conclusions Five molecular markers available for mark-er-assisted selection were selected for tracking Qpm.sxn-1B and Qpm.sxn-2B in the program. The identification of this novel newly discovered QTL and markers reported in this study will be useful for marker-assisted selection of powdery mildew resistance. [ABSTRACT FROM AUTHOR]